序言
最近因为工作需要在阅读flink checkpoint处理机制，学习的过程中记录下来，并分享给大家。也算是学习并记录。
目前公司使用的flink版本为1.11。因此以下的分析都是基于1.11版本来的。
在分享前可以简单对flink checkpoint机制做一个大致的了解。
Flink checkpoint 机制介绍
Flink的checkpoint的过程依赖于异步屏障快照算法，该算法在《Lightweight Asynchronous Snapshots for Distributed Dataflows》这篇paper中被提出。理解了这篇paper也就明白了flink的chekpoint机制。paper整体来说比较简单易懂，下面简单介绍下paper的大体内容和核心的算法。
[1] 引用：Flink Checkpoint原理解析 - 知乎
代码分析
Flink checkpoint 的触发是通过CheckpointCoordinator 的定时线程完后。
private ScheduledFuture<?> scheduleTriggerWithDelay(long initDelay) {return timer.scheduleAtFixedRate(new ScheduledTrigger(),initDelay, baseInterval, TimeUnit.MILLISECONDS);}之后通过snapshotTaskState RPC的调用来实现触发checkpoint的
代码中遍历executions 来触发checkpoint，那么executions是什么东西呢？
Flink 代码中维护了一个叫tasksToTrigger的数组。
这个地方向前追溯，可以一直到jobgrap的生成。从名字和代码就可以看出，这个里面存的是没有inputchannel的节点，source节点没有inputchannel，所以回答上面的问题，executions 中是source节点，也就是做checkpoint 时 checkpointcoordinate 会给source节点发送rpc。
通过一个很长亮度的调用，最后到了SubtaskCheckpointCoordinatorImpl 中的
public void checkpointState(CheckpointMetaData metadata,CheckpointOptions options,CheckpointMetricsBuilder metrics,OperatorChain<?, ?> operatorChain,Supplier<Boolean> isCanceled) throws Exception {checkNotNull(options);checkNotNull(metrics);// All of the following steps happen as an atomic step from the perspective of barriers and// records/watermarks/timers/callbacks.// We generally try to emit the checkpoint barrier as soon as possible to not affect downstream// checkpoint alignmentsif (lastCheckpointId >= metadata.getCheckpointId()) {LOG.info("Out of order checkpoint barrier (aborted previously?): {} >= {}", lastCheckpointId, metadata.getCheckpointId());channelStateWriter.abort(metadata.getCheckpointId(),new CancellationException("checkpoint aborted via notification"),true);checkAndClearAbortedStatus(metadata.getCheckpointId());return;}// Step (0): Record the last triggered checkpointId and abort the sync phase of checkpoint if necessary.lastCheckpointId = metadata.getCheckpointId();if (checkAndClearAbortedStatus(metadata.getCheckpointId())) {// broadcast cancel checkpoint marker to avoid downstream back-pressure due to checkpoint barrier align.operatorChain.broadcastEvent(new CancelCheckpointMarker(metadata.getCheckpointId()));LOG.info("Checkpoint {} has been notified as aborted, would not trigger any checkpoint.", metadata.getCheckpointId());return;}// if checkpoint has been previously unaligned, but was forced to be aligned (pointwise// connection), revert it here so that it can jump over output dataif (options.getAlignment() == CheckpointOptions.AlignmentType.FORCED_ALIGNED) {options = options.withUnalignedSupported();initInputsCheckpoint(metadata.getCheckpointId(), options);}// Step (1): Prepare the checkpoint, allow operators to do some pre-barrier work.// The pre-barrier work should be nothing or minimal in the common case.operatorChain.prepareSnapshotPreBarrier(metadata.getCheckpointId());// Step (2): Send the checkpoint barrier downstreamLOG.debug("Task {} broadcastEvent at {}, triggerTime {}, passed time {}",taskName,System.currentTimeMillis(),metadata.getTimestamp(),System.currentTimeMillis() - metadata.getTimestamp());CheckpointBarrier checkpointBarrier =new CheckpointBarrier(metadata.getCheckpointId(), metadata.getTimestamp(), options);operatorChain.broadcastEvent(checkpointBarrier, options.isUnalignedCheckpoint());// Step (3): Register alignment timer to timeout aligned barrier to unaligned barrierregisterAlignmentTimer(metadata.getCheckpointId(), operatorChain, checkpointBarrier);// Step (4): Prepare to spill the in-flight buffers for input and outputif (options.needsChannelState()) {// output data already written while broadcasting eventchannelStateWriter.finishOutput(metadata.getCheckpointId());}// Step (5): Take the state snapshot. This should be largely asynchronous, to not impact// progress of the// streaming topologyMap<OperatorID, OperatorSnapshotFutures> snapshotFutures = new HashMap<>(operatorChain.getNumberOfOperators());try {if (takeSnapshotSync(snapshotFutures, metadata, metrics, options, operatorChain, isCanceled)) {finishAndReportAsync(snapshotFutures, metadata, metrics, options);} else {cleanup(snapshotFutures, metadata, metrics, new Exception("Checkpoint declined"));}} catch (Exception ex) {cleanup(snapshotFutures, metadata, metrics, ex);throw ex;}}代码中可以看到构造了CheckpointBarrier， source将barrier当成数据广播给下游的所有节点。使用的方法就是operatorChain.brodacastEvent()。这里就回到最开始提到的异步屏障快照算法。
下游收到了barrier，如何进行快照处理的？flink同时有多种类型的checkpoint，他们分别的处理时机是啥，后面我会进一步进行代码分析。
CheckpointBarrier checkpointBarrier =new CheckpointBarrier(metadata.getCheckpointId(), metadata.getTimestamp(), options);operatorChain.broadcastEvent(checkpointBarrier, options.isUnalignedCheckpoint());
)
